The role of sarcopenic obesity for the prediction of prognosis of patients with gastrointestinal cancer

Abstract Background Sarcopenic obesity (SO) in patients with gastrointestinal cancer is associated with a poor prognosis. We aimed to investigate the prognostic impact of SO in patients with gastrointestinal cancer, as well as the diagnostic cut‐off value of SO in patients with gastrointestinal cancer among Chinese population. Methods We conducted a consecutive cohort study. Between January 2017 and January 2019, 289 patients diagnosed with gastrointestinal cancer were included in our study. Skeletal muscle area, total fat area, and subcutaneous fat area were measured by CT scan. All patients were followed up for 5 years. Receiver operating characteristic curves (ROC) were adopted to determine the cut‐off values of visceral fat obesity for the prediction of sarcopenia. Based on the cut‐off values, patients with sarcopenia combined with visceral fat obesity were divided into the SO group, and the others were divided into the non‐sarcopenic obesity (NSO) group. Kaplan–Meier curves and univariate and multivariate Cox proportional hazard models were employed to explore the associations of body composition profiles with 5‐year overall survival and disease‐specific survival. Results Obtained from Youden's Index for ROC for the prediction of 5‐year survival, skeletal muscle mass index (SMI) ≤40.02 cm2/m2 with VFA ≥ 126.30 cm2 in men and SMI ≤32.05 cm2/m2 with VFA ≥72.42 cm2 in women indicate a risk of poor prognosis in patients diagnosed with gastrointestinal cancer. Patients with SO had poorer 5‐year overall survival (OS) than patients with NSO (6.74% vs. 82.84%, p < 0.001), and poorer 5‐year DFS (6.74% vs. 81.82%, p < 0.001). In multivariate analysis, we found that the long‐term mortality risk was approximately 13‐fold higher among patients in the SO group compared to those with no conditions. Conclusions Preoperative assessment of SO is useful not only for monitoring nutritional status but also for predicting 5‐year OS in gastrointestinal cancer patients.


| INTRODUCTION
The global incidence of gastrointestinal cancer has significantly increased in recent years, leading to high mortality and morbidity rates. 1 The prognosis of gastrointestinal cancer imposes a heavy economic and psychological burden on patients and society. 2 Nutritional imbalance is a common issue in patients with gastrointestinal cancer and has been reported to be closely associated with poor prognosis such as wound infections, anastomotic leakage, and an increased probability of conversion to open surgery. 3Therefore, early nutritional screening and rational nutritional intervention to correct malnutrition in patients with gastrointestinal cancer are crucial.
Sarcopenic obesity (SO), the state of having both sarcopenia and obesity, has been linked to adverse prognosis among patients with gastrointestinal cancer. 4Sarcopenia affects approximately 40%-80% of patients with gastrointestinal cancers. 5Gastrointestinal cancer mainly affects the digestive tract leading to inadequate dietary intake. 6,7revious research has proved that sarcopenia was an independent risk factor for poor outcome in individuals with various types of cancer and can be used to predict overall survival (OS). 8High visceral fat area (VFA) is significantly related to pro-inflammation and is considered an indicator associated with poorer colon cancer outcomes and a worse prognosis in colorectal, 9 esophageal, 10 and gastric cancers. 11he nutritional status of patients was often easily neglected by clinicians, leading to delayed provision of necessary nutritional support.Particularly in patients with SO, without a computed tomography (CT) scan, these patients are often under-diagnosed as not at nutritional risk because they do not have significant short-term weight changes and visible signs of wasting.Malnutrition compromises patient outcomes, and failure to provide timely nutritional intervention can have serious consequences.Therefore, early nutritional screening and timely detection of SO patients is essential in helping them reverse malnutrition. 12revious studies primarily concentrated on Caucasians, while the human body composition of different populations varies widely.Currently, there is no consistent diagnostic cut-off value for skeletal muscle mass index (SMI) in the Chinese population, and the diagnostic cut-off values for visceral fat obesity differ among different populations.In this study, we aim to investigate the diagnostic cut-off value of SO in patients with gastrointestinal cancer in the Chinese population and explore the prognostic effects of SO in patients with gastrointestinal cancer.

| Participants
This trial recruited gastrointestinal cancer patients from the Affiliated Drum Tower Hospital of Nanjing University Medical College in Nanjing, China, between January 2017 and January 2019.Inclusion criteria were as follows: (1) all patients were newly diagnosed and did not receive surgery, chemotherapy, radiation, or neoadjuvant therapy; (2) radical surgery in our hospital; (3) basic information, medical history, auxiliary examination, nutritional indexes, and other data were complete.Exclusion criteria were as follows: (1) under the age of 18; (2) severe edema, such as pleural effusion or ascites, cardiac or kidney failure, cirrhosis, and the use of diuretic drugs; (3) patients with distant metastases; (4) refuse to participate or unable to cooperate, use of lipid-regulating drugs, protein supplements, etc., in the last 3 months.This study was approved by the Clinical Research Ethics Committee of Nanjing Drum Tower Hospital.Written informed consent was obtained from all participants.Among the eligible patients, 289 patients with gastrointestinal cancers participated in the final study.
13-fold higher among patients in the SO group compared to those with no conditions.

Conclusions:
Preoperative assessment of SO is useful not only for monitoring nutritional status but also for predicting 5-year OS in gastrointestinal cancer patients.

K E Y W O R D S
gastrointestinal cancer, nutrition, sarcopenia, sarcopenic obesity | 3 of 11 CHEN et al.

| CT anthropometric measurements
All participants underwent CT scans within the first 24 h after admission.The methods for analyzing body composition using CT scanning were adapted from previously published protocols. 13Skeletal muscle area, measured at the level of the third lumbar vertebra (L3), is an accurate surrogate for total skeletal muscle mass 14 and was selected for analysis using Matlab software (MathWorks, USA).The skeletal muscle area was manually sketched and segmented using Hounsfield units (HU) ranging from −29 to 150 to represent skeletal muscle tissue.The radiation attenuation was expressed as the mean HU of the compartment.The SMI was defined as the area of skeletal muscle mass, usually calculated as the area relative to the patient's height (SMI = skeletal muscle mass at L3 [cm 2 ]/square of body height [m 2 ]), which is then used to assess patients for sarcopenia.The VFA was measured at the level of the umbilical slice level on the CT image, while the subcutaneous fat area (SCFA) was measured on CT slices at the same location.The VFA was manually outlined and calculated using MATLAB software (MathWorks, Massachusetts, USA) and was calculated within the range of HU from −150 to −50.CT measurements were performed independently by two doctors who have received medical training and worked independently from one another.They were blinded to the patients' personal information.

| Data collection and follow-up
The patients' demographic details including age, height, weight, education level, smoking, and drinking history, etc., were collected from the medical card.Tumor stage classification followed the criteria set by the American Joint Committee on Cancer, 15 devoid of any subjective evaluations.The WHO/Eastern Cooperative Oncology Group scale was used to grade the performance status (0 = normal performance, 4 = bed-bound).Tumor markers were assessed upon admission, with parameters including carcinoembryonic antigen, carbohydrate antigen 125, carbohydrate antigen 199, carbohydrate antigen 724, and carbohydrate antigen 242.A fasting blood sample was collected during the first admission for laboratory testing to observe the impact of covariates on the study outcomes.
The follow-up time was defined as from the surgery date up to the death or the end of follow-up (August 31, 2022), whichever came first.Patients were monitored via telephone every 3 months for 2 years and every 6 months thereafter for up to 5 years under an established follow-up program to gather relevant information on clinical outcomes.The primary endpoints were OS and disease-free survival (DFS).The secondary endpoint was medically confirmed recurrence.

| Statistical analysis
Statistical analyses were performed using SPSS software (version 22.0, IBM, USA) and graphs were created with Prism version 8.0.2 (GraphPad).Continuous data were expressed as either the mean ± standard deviation or median (25th percentile and 75th percentile).The Mann-Whitney U-test or independent Student t-test were used to compare continuous variables.Categorical variables were analyzed with the χ 2 test.Receiver operating characteristic curves (ROC) were utilized to determine the cutoff values for both visceral fat obesity and sarcopenia.The ideal cut-point was established using the Youden Index (Youden Index = sensitivity + specificity −1).According to the cut-off values of the body composition profiles, the population was divided into two groups: SO and nonsarcopenic obesity (NSO) groups.Kaplan-Meier method and log-rank test were used to investigate the relationships between body composition profiles and both the 5-year OS and DFS rates.Univariable and multivariate regression was undertaken using Cox proportional hazards regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), and the forward LR stepwise selection method was used to assess the potential interaction effects of variables in the multivariate model.A two-sided p < 0.05 was considered statistically significant.

| Baseline
Between January 2017 and January 2019, 372 patients with gastrointestinal cancer were screened for eligibility and 289 of them were included in this study (Figure 1).The baseline characteristics of the patients were presented in Table 1.
There were 183 males and 106 females enrolled in this study, their mean age was 67.6 ± 11.4 years old.A total of 116 tumors (40.1%) were gastric cancer and 173 tumors (59.9%) were colorectal cancer.Patients were followed up clinically for a median of 52 (IQR: 48, 58) months.

| Cut-off values for visceral fat obesity and sarcopenia
Utilizing ROC curves to predict 5-year OS and Youden's Index, we identified the sex-specific cut-off values for visceral fat obesity and sarcopenia (Figure 2).Sarcopenia was defined as SMI ≤40.02cm 2 /m 2 in men and SMI ≤32.05 cm 2 / m 2 in women.Visceral fat obesity was defined as VFA ≥126.30cm 2 in men and VFA ≥72.42 cm 2 in women in the present study (Table 3).Sarcopenia patients accounted for 27.34% of the study population and 35.99% of patients were visceral fat obese (Table 2).
Based on the cut-off values of the body composition profiles, patients with sarcopenia combined with visceral fat obesity were divided into the SO group and the others were divided into the NSO group.In this study, 22 individuals (7.61%) were identified with SO, 79 (27.34%) were diagnosed with sarcopenia, and 104 patients (35.99%) experienced visceral fat obesity (Table 2).There were no statistically significant differences were found in the demographic and clinic opathological data between the SO and NSO groups (Table 1).The median duration of follow-up within the SO group was significantly lower than that of the NSO group (51 (IQR: 19, 54) vs. 52(IQR: 48.5, 59), p = 0.034).The DFS was also significantly lower in the SO group compared to the NSO group (p = 0.034).

Cox regression of body composition profiles with OS and DFS for gastrointestinal cancer
Univariable analysis revealed that presence of SO was significantly associated with poor OS (HR 8.904, 95% CI 4.970-15.954,p = 0.000).In addition, low Alb (HR 0.890, 95% CI 0.823-0.962,p = 0.003), low Hb (HR 0.984, 95% CI 0.973-0.995,p = 0.004), were significantly associated with poor OS (Table 4).Factors associated with DFS were shown in Table 5.In the multivariate regression model containing the statistical significantly variables, we found that presence of SO (HR 13.529, 95% CI 7.064-25.912,p = 0.000), was risk factor for OS, tumor stage III was associated with a 4.894-fold increase overall risk of death compared to patients with tumor staged I (HR 4.849, 95% CI 1.850-12.709,p = 0.027), Alb (HR 0.899, 95% CI 0.815-0.991,p = 0.032) was protective factors for OS (Table 4).Multivariate analysis identified the presence of SO (HR SO is a state characterized by decreased skeletal muscle mass and visceral fat mass. 16Our results was in consistency with previous conclusions that patients with cancer who develop SO tend to have a poorer prognosis. 17,18A meta-analysis conducted by Wang et al. on 8729 patients who underwent surgery for gastrointestinal cancer revealed that SO was associated with an increased risk of postoperative complications and a lower survival rate in patients with gastrointestinal cancer. 19Several studies have found that the presence of SO in cancer patients is correlated with negative outcomes.Kobayashi et al. discovered that preoperative SO was a significant risk factor for mortality and HCC recurrence following hepatectomy for HCC. 20Kim et al. noted that SO was an independent risk factor for increased mortality in patients suffering from gastric cancer. 21n our study, both of VFA and SMI were significantly associated with OS and DFS, which was corroborated with previously reported studies.Gastrointestinal cancers, such as stomach and colorectal cancer, have a high incidence of sarcopenia. 22Sarcopenia is characterized as a clinical indication of the cancer cachexia syndrome 23 and may lead to the loss of muscle strength, impaired immune function and reduced tolerance to cancer treatments such as chemotherapy or surgery.These factors contribute to an increased risk of complications in patients with gastrointestinal cancer. 23Visceral fat obesity is associated with the development of chronic inflammation and insulin resistance, both of which are critical in both tumor development and further progression. 24It has been documented that visceral fat obesity is a risk factor for different cancer complications. 25,26tudies have increasingly recognized the importance of The ROC curves of body composition profiles for the prediction of 5-year mortality in males and females.L3-SMI, L3-skeletal muscle index, VFA, visceral fat area.

Variable
Overall muscular fatty infiltrations for the loss of skeletal muscle function. 27Fat accumulation in muscle tissue initiates a pro-inflammatory response and oxidative stress, consequently resulting in mitochondrial dysfunction, impaired insulin signaling, and subsequent muscle atrophy. 28Sarcopenia and visceral fat obesity are both clinically detectable and diagnosable.To combine skeletal muscle marker with visceral fat marker could comprehensively reflect body immune system and insulin resistance.Thus, patients with SO display an increased susceptibility to tumor development and an unfavorable prognosis.In previous studies of SO cut-off values, the study populations were selected from groups with heterogeneous characteristics.0][31] However, the absence of a universally applicable cut-off value for different diseases remains a contentious issue due to the limited transferability of utilization among heterogeneous patient cohorts in different cancer patient populations, especially in Chinese population.In our study, we performed ROC analysis on our own data to find a Chinese specific cut-off value for the diagnostic threshold that is appropriate for the population of patients with gastrointestinal tumors in Eastern China.This highlights the need for further researches to better understand the underlying mechanisms behind this condition.Sarcopenia is generally linked to weight loss, while visceral fat obesity is associated with weight gain.However, patients with SO who do not undergo a CT scan are often misdiagnosed as not being at nutritional risk, as they lack significant short-term weight changes and visible signs of wasting.Without appropriate nutritional interventions, malnutrition can have a detrimental effect on patient outcomes and result in severe consequences.The implementation of appropriate testing can facilitate the achievement of early detection, early diagnosis, and timely early nutritional intervention, thereby promoting the likelihood of improved clinical outcome results.Consequently, the timely identification and screening of malnourished patients with SO is imperative to enable them to reverse their malnutrition. 12ur study has revealed that SO is associated with a poor prognosis in gastrointestinal cancers.It is recommended that clinicians raise awareness of this indicator in clinical practice in order to facilitate the implementation of early nutritional interventions for patients with SO, and thereby enhance patient prognosis.
Interestingly, there were no statistically significant differences in demographic and clinicopathological data between the SO and NSO groups in our study.This phenomenon could elucidate why BMI is an unreliable T A B L E 3 Diagnostic accuracy of body composition profiles to predict overall survival.prognostic indicator for cancer surgery, as it fails to account for disparities in fat or muscle mass distribution 32 This observation has also been referred to as the obesity paradox in cancer, as high sex-specific BMI levels do not always correlate with poor cancer prognosis. 10Combined with a state of visceral fat obesity, this can obscure reduced muscle mass due to malnutrition.SO may be influenced by factors beyond conventional risk factors in cancer patients, such as age, gender, and body mass index.Several studies have described that higher subcutaneous fat area has a protective association with the deleterious inflammatory outcomes associated with visceral fat. 33,34any patients with normal BMI might actually harbor SO to various degrees, before it progresses to full-blown severe sarcopenia. 16It is theoretically possible that tumor staging may affect the composition of human body components. 35,36However, there may be no distributional differences in this study due to the relatively small sample size and other issues.

Males
Our study has some limitations.First, being a singlecenter study, it may have a selection bias.Large-sample multicenter studies are required to validate our conclusions, as well as a development cohort and a validation cohort.Our future work will focus on expanding the sample size and incorporating more relevant influencing factors affecting prognosis.Furthermore, we will obtain patients' consent to obtain blood samples during the study period to improve the genomics analysis.Additionally, using only the cross-sectional skeletal muscle area for SMI calculation may have potentially led to underestimated prevalence estimates.More research is required to assess the impact of muscle strength on the survival of patients with gastrointestinal cancer.This establishes a more accurate, stable, and reliable prediction model that can be applied to clinical practice.Finally, specific follow-up on nutritional support was not included, making it impossible to determine whether changes in nutritional status have an effect on SO.This highlights the necessity for further research to better comprehend the potential influence of nutritionrelated factors behind this condition.

| CONCLUSION
Patients with SO had worse 5-year OS and DFS.Sarcopenia is diagnosed when SMI ≤40.02 cm 2 /m 2 in men and SMI ≤32.05 cm 2 /m 2 in women.Visceral fat obesity was diagnosed when VFA ≥126.30cm 2 in men and VFA ≥72.42 cm 2 in women.Preoperative assessment of SO is beneficial not only for monitoring nutritional status but also for predicting long-term OS in patients with gastrointestinal cancer.Early intervention for SO patients is helpful to improve the clinical prognosis of patients, bolster their quality of life, cut down on medical expenses and recurrent hospitalization, and assuage the medical and economic burden on the community.

F I G U R E 1
Flow diagram of the research.

N = 289 NSO n = 267 SO n = 22 p value
Body composition ssprofiles in patients with gastrointestinal cancer.
Note: Data are presented as mean ± standard deviation.Abbreviations: SC, subcutaneous fat; SMI, skeletal muscle index; VF, visceral fat.*p < 0.001.T A B L E 2 Cox hazard regression analysis for factors associated with 5-year overall survival.: Alb, albumin; BMI, body mass index; SMI, skeletal muscle index; VF, visceral fat.*p < 0.05 or p < 0.001.Cox hazard regression analysis for factors associated with 5-year disease-specific survival.
T A B L E 4AbbreviationsT A B L E 5Abbreviations: Alb, albumin; BMI, body mass index; SMI, skeletal muscle index; VF, visceral fat.*p < 0.05 or p < 0.001.